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How robust is the SVM wound segmentation?

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2 Author(s)
Kolesnik, M. ; Fraunhofer Inst. for Appl. Inf. Technol., Sankt Augustin ; Fexa, A.

This paper investigates the robustness of automatic wound segmentation. The work builds upon an automatic segmentation procedure by the support vector machine (SVM)-classifier presented in [M. Kolesnik et al. (2004), (2005)]. Here we extend the procedure by incorporating textural features and the deformable snake adjustment to refine SVM-generated wound boundary. The robustness of SVM-based segmentation is tested against different feature spaces using a long sample of training images featuring a broad variety of wounds' appearance. Recommendations drawn from these experiments provide a useful guideline for the development of a software support system for the visual monitoring of chronic wounds in wound care units

Published in:

Signal Processing Symposium, 2006. NORSIG 2006. Proceedings of the 7th Nordic

Date of Conference:

7-9 June 2006